An Object-Oriented Change Detection Method Based on Multi-Feature Fusion

A change detection, object-oriented technology, applied in the field of remote sensing, can solve the problem of low accuracy of detection results, and achieve the effect of improving accuracy

Active Publication Date: 2019-03-01
THE HONG KONG POLYTECHNIC UNIV SHENZHEN RES INST
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Problems solved by technology

[0003] The purpose of the present invention is to provide an object-oriented change detection method that integrates multiple

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  • An Object-Oriented Change Detection Method Based on Multi-Feature Fusion
  • An Object-Oriented Change Detection Method Based on Multi-Feature Fusion
  • An Object-Oriented Change Detection Method Based on Multi-Feature Fusion

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[0058] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0059] In order to illustrate the technical solution of the present invention, the following will be described in detail in conjunction with specific drawings and embodiments.

[0060] see figure 1 , the embodiment of the present invention provides an object-oriented change detection method that fuses multiple features, including the following steps:

[0061] S101. Image preprocessing: preprocessing the two-phase multispectral remote sensing images, the preprocessing includes image matching and radiation correction;

[0062] S102. Texture feature extraction: extract texture features required for ...

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Abstract

The invention is applicable to the field of remote sensing technology, and provides an object-oriented change detection method based on multi-feature fusion, comprising the following steps of: S101, image preprocessing; S102, texture feature extraction; S103, image segmentation; S104, feature extraction of that object; S105, generating a difference image; S106, acquire an initial change detectionresult; S107, calculating feature weights; S108, the object change detection result is obtained, and each detected object is clustered into two classes of variable and invariant by fusing multi-dimensional features through weighted fuzzy C-means method. As that embodiment of the invention carry out the processing of the above step on the two-phase images, analyze and determine the weight of each dimension feature, and the weights of each dimension feature are extracted by Relief algorithm, The weighted fuzzy C-means method is formed by adding weights into the fuzzy C-means method, and the weighted fuzzy C-means method is used to fuse the multi-dimensional features, and the detection objects are clustered into two categories: variable and invariant, which effectively fuses the different features to carry out object-oriented change detection and improves the accuracy of the change detection results.

Description

technical field [0001] The invention belongs to the technical field of remote sensing, in particular to an object-oriented change detection method with fusion of multiple features. Background technique [0002] In remote sensing images, change detection using objects as the basic unit can reduce the impact of noise on the accuracy of change detection results, especially when high-resolution remote sensing images are used for change detection. In traditional object-oriented change detection, spectral features are usually used for change detection. Due to the complexity of ground objects and the limitation of imaging conditions, remote sensing images have the phenomenon of "same spectrum but different spectrum" and "same object with different spectrum". The test results have a greater impact. Therefore, the detection accuracy of this kind of change detection using only spectral features is relatively low, and the above deficiencies need to be improved. Contents of the inven...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/54
CPCG06V10/20G06F18/232
Inventor 史文中蔡利平
Owner THE HONG KONG POLYTECHNIC UNIV SHENZHEN RES INST
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